Did China’s ICO ban alter the Bitcoin market?

Okorie, David Iheke; Lin, Boqiang

doi:10.1016/j.iref.2020.05.016

Cited by 14 publications

(7 citation statements)

References 29 publications

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“…In contrast, investors with lower risk aversion can diversify their portfolios using BTC and expect higher returns. Similar conclusions were obtained by Okorie (2020), who examined the diversification possibilities of BTC, as well as shares from the S&P500 stock index in 2016-2018. He confirmed that BTC is a profitable investment instrument, and also allows for a good diversification of equity portfolios.…”

Section: Literature Reviewsupporting

confidence: 80%

Investments in the cryptocurrency market or the commodity exchange. Which is more efficient?

Kozak

Gajdek

2021

ZN MWSE w Tarnowie

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Cryptocurrencies have become an essential element of the global financial system, and in recent years also a frequent investment tool. The aim of the study is to check whether investments in cryptocurrencies are more effective than in commodities on commodity exchanges. The study was conducted based on the daily quotations of the analyzed instruments in 2011–2020. The investment efficiency level was estimated using Sharpe’s and Sortino’s indicators. The research results showed that, on average, over the entire period under study, investments in cryptocurrencies were burdened with the highest risk, but at the same time achieved the highest daily rates of return. As a result, they were much more effective investment tools than gold, silver and WTI. The advantage of cryptocurrencies could be due to the long-term persistence of ultra-low interest rates and the reduced attractiveness of investment in debt securities. Bitcoin and etherum with the largest shares in cryptocurrency market capitalization have proven to be the most effective investment tools.

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Section: Literature Reviewsupporting

confidence: 80%

Investments in the cryptocurrency market or the commodity exchange. Which is more efficient?

Kozak

Gajdek

2021

ZN MWSE w Tarnowie

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“…However, as an alternative to the network modelling connectedness (Okorie, 2020c; Okorie & Lin, 2020a), we move further to adopt the MGARCH − GJR − BEKK ( C , D ) volatility model in Equation (5) to factor the role of asymmetric volatility effects between the markets using the asymmetric component (Glosten et al, 1993) in the volatility spillover model analysis for the oil prices and the Nigerian stock market return. The MGARCH − GJR − BEKK ( C , D ) has been adopted by several researchers like Okorie (2020a, 2020b), Okorie and Lin (2020c), Tule et al (2017), and others.

a_{t} = {bold-italicH}_{t}^{\frac{1}{2}} z_{t}

H_{t} = D_{t} R_{t} D_{t}

H_{t} = C^{T} bold-italicC + \sum_{i = 1}^{C} {bold-italicX}_{bold-italici}^{T} a_{t - 1} a_{t - 1}^{T} X_{i} + \sum_{i = 1}^{D} {bold-italicY}_{bold-italici}^{T} H_{t - i} Y_{i}

H_{t} = C^{T} bold-italicC + \sum_{i = 1}^{C} {bold-italicX}_{bold-italici}^{T} a_{t - 1} a_{t - 1}^{T} X_{i} + \sum_{i = 1}^{D} <...

…”

Section: Data and Empirical Strategymentioning

confidence: 99%

“… This article takes a new dimension into considering percentage changes in both markets (Okorie & Lin, 2020a, 2020b, 2020c), independent of the exchange rate influences, to nullify the effects of the Nigerian Naira (NGN) and the United States Dollar (USD) exchange rate in the analysis of the relationship between both markets. In other words, this article aims to study the information spillover between the NSE and global crude oil markets without the effects of the exchange rates, different from the existing studies.…”

Section: Introductionmentioning

confidence: 99%

“…Section 4 discusses the results and intuitions and in Section 5, we conclude. Okorie and Lin (2020c) show that the global crude oil market, WTI, is a substantial net information receiver in the Nigerian oil and gas industry. Tule et al (2017) investigated the volatility spillover from the Brent oil prices and that of WTI oil prices to the Nigerian Sovereign Bond market using the Vector Auto-Regressive Moving Average Asymmetric Generalized Auto-Regressive Conditional Heteroscedasticity (VARMA-AGARCH) model.…”

Section: Introductionmentioning

confidence: 99%

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Crude oil market and Nigerian stocks: An asymmetric information spillover approach

Okorie

Lin

2020

Int. J Fin Econ

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This article examines the nature of information spillovers, in return and volatility, that exists between the full index stock of the Nigerian stock exchange (NSE) and the crude oil markets (Brent and West Texas Intermediate (WTI) oil markets). We adopted the asymmetric VAR − MGARCH − GJR − BEKK model and found evidence of unidirectional return spillover from the Brent oil market to the NSE and a bidirectional return spillover between the NSE market and the WTI oil market. The response of the WTI market to a shock on the NSE market is rather short-lived. There exists strong evidence of a lead-lag relationship between the crude oil market and the NSE market wherein the crude oil market leads or drives the NSE market return fluctuations. For both crude oil markets, the Brent and the WTI markets, there exists a bidirectional volatility spillover between the NSE index and the crude oil markets, as well as significant asymmetric shocks. Practical policy implications and recommendations were made, based on the findings.

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“…There are 30,000+ companies registered as blockchain businesses in China [15]. On the other hand, politically, China has been actively imposing various bans on Bitcoin, cryptocurrency in general and ICO (Initial Coin Offering), especially post-2017 [16][17][18]. While many countries are employing various kinds of bans on cryptocurrencies, China's actions have arguably been the most influential in cryptocurrency markets, and often are viewed as controversial.…”

Section: Introductionmentioning

confidence: 99%

Bitcoin and Fiat Currency Interactions: Surprising Results from Asian Giants

2021

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This study examines the interaction of Bitcoin with fiat currencies of three developed (euro, pound sterling and yen) and three emerging (yuan, rupee and ruble) market economies. Empirical investigations are executed through symmetric, asymmetric and non-linear causality tests, and Markov regime-switching regression (MRSR) analysis. Results show that Bitcoin has a causal nexus with Chinese yuan and Indian rupee for price and various return components. The MRSR analysis justifies these findings by demonstrating the presence of interaction in contractionary regimes. Accordingly, it can be stated that when markets display a downward trend, appreciation of the Chinese yuan and Indian rupee positively and strongly affects the value of Bitcoin, possibly due to the market timing. The MRSR analysis also exhibits a transition from a tranquil to a crisis regime in March 2020 because of the pandemic. However, a shorter duration spent in the crisis regime in 2020 indicates the limited and relatively less harmful effect of the pandemic on the cryptocurrency market when compared to the turmoil that occurred in 2018.

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Did China’s ICO ban alter the Bitcoin market?

Cited by 14 publications

References 29 publications

Investments in the cryptocurrency market or the commodity exchange. Which is more efficient?

Investments in the cryptocurrency market or the commodity exchange. Which is more efficient?

Crude oil market and Nigerian stocks: An asymmetric information spillover approach

Bitcoin and Fiat Currency Interactions: Surprising Results from Asian Giants

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